A silicon Hall sensor SoC for current sensors

Girgin, Alper; Bilmez, Melih; Amin, Hamid Yadegar; Karalar, Tufan Coşkun

doi:10.1016/j.mejo.2019.04.020

Cited by 21 publications

(9 citation statements)

References 7 publications

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“…Similar systems have been used to monitor loading and unloading of spinal columns [27] and in orientation resolution of a spherical actuator [28]. Since Hall effect sensors and sensor arrays have been shown to have high accuracy for distance/orientation measurement [25,28,29], the use of Hall effect sensors in the continuum limbs of our robotic limb offers a small form factor but with the potential for high accuracy.…”

Section: Hall Effect Sensor Feedbackmentioning

confidence: 99%

Design of a Hall effect sensor controlled brittle star inspired composite robotic limb

Mack

Alam

2022

Eng. Res. Express

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This paper elucidates a method of actuation and feedback for hard-soft composite continuum pentapod appendages to enable both kinematic accuracy and gait. A feedback mechanism based on Hall effect sensors is integrated within a hard exterior/soft interior composite robotic limb, which is unaffected by actuator slippage, and provides accurate (sub $2^\circ$) end point measurements. The proposed method for actuation uses two actuators to control a full semi-spherical range of motion, an improvement to the use of three actuators more commonly reported in the literature. When applied to enable the gait of a complete brittle star inspired pentapod, we find that our design reaches a momentum of 0.52$kg \cdot m/s$, surpassing the momentum of previously reported untethered starfish inspired pentapods by 3.7 times.

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Section: Hall Effect Sensor Feedbackmentioning

confidence: 99%

Design of a Hall effect sensor controlled brittle star inspired composite robotic limb

Mack

Alam

2022

Eng. Res. Express

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“…The hall effect sensor is a transducer that could change the amount of magnetical field into the electrical field in the form of current. This type of sensor in its operation detect proximity, the existence or the absence of a magnetic field from an object [9]- [11].…”

Section: Acs 712 Current Sensormentioning

confidence: 99%

Monitoring and Controlling The Hybrid System Using The Internet Of Things For Energy Transaction

Wibowo

Lestari

2019

FESPE

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The electrical energy is an energy that is needed by the people. Theelectrical energy, to date, came from several power plants, such aselectric steam power plants and diesel power plants. The communitymust pay the service provider, such as the State ElectricityCompany (PLN) with a rising cost, to obtain electrical energy.However, there were other alternative energies, for example, solarpower plants and windmill power plants. The hybrid system is acombination of two or more different energy sources to meet thedemand. The hybrid system was also expected to solve the problemthat might arise in utilizing other energies, the site condition, andthe unpredicted situation on the power plant. The solution to theseproblems was a hybrid using a monitoring device with ACS 712sensor current parameter, ZMPT101B voltage sensor, LDR solarsensor, hybrid electrical energy power, controller for four electricalsource inputs and three electrical sources for the output load. Thedevice used Arduino Mega 2560 for data processing, ESP 8266 asthe module to connect the device to the internet network and relayas the control actuator. Monitoring and controlling the device usedthe internet network and the implementation of the Internet ofThings (IoT) on the hybrid system plants (PLN, generator, solarpower plant, windmill power plant) that was integrated into thewebsite. The overall test resulted in the comparison average errorvalue between the device and the measuring instrument of thecurrent, voltage, and power. The test also resulted in the averageerror value of the response time for the four input contacts and threeoutput contacts. The average error value of the current was 2.13%,the average error value of the voltage was 0.7%, and the averageerror value from the power parameter was 0%. Meanwhile, theaverage error value of response time was 0.23 seconds. Based onthe above results, it can be concluded that the monitoring andcontrolling system from the website with the implementation of theIoT in the hybrid power system was worked following the design.

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“…17,18 Hall sensor is small and has fast response speed but has low sensitivity. [19][20][21][22] AMR has the advantages of noncontact operation, easy maintenance, and robustness to contamination 23,24 and they are much more sensitive than any semiconductor sensor, 25 which is usually used to measure MFD of 0.2 mT to 2.5 mT. SQUID uses the principle of Josephson effect to measure the magnetic eld.…”

Section: Introductionmentioning

confidence: 99%